AIMC Topic: Machine Learning

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From dry eye to depression: a machine learning-based framework for predicting adolescent mental health.

BMC medical informatics and decision making
BACKGROUND: Adolescent depression is a major public health concern. Physical health indicators are rarely included in risk tools. We examined whether adding dry eye disease (DED) to psychosocial and behavioral factors improves prediction of depressiv...

TransST: transfer learning embedded spatial factor modeling of spatial transcriptomics data.

BMC bioinformatics
BACKGROUND: Spatial transcriptomics have emerged as a powerful tool in biomedical research because of its ability to capture both the spatial contexts and abundance of the complete RNA transcript profile in organs of interest. However, limitations of...

An improved facial emotion recognition system using convolutional neural network for the optimization of human robot interaction.

Scientific reports
Artificial intelligence (AI) has been effectively augmenting the features of robotics applications, including surveillance, medical support, aid services for the elderly or disabled, and many more uses. Most robotics applications need a variety of hu...

Efferocytosis-related signatures identified via Single-cell analysis and machine learning predict TNBC outcomes and immunotherapy response.

Scientific reports
Triple-negative breast cancer (TNBC) is characterized by poor prognosis and limited targeted treatment options. Efferocytosis, an essential immune mechanism for the clearance of apoptotic cells, is increasingly recognized as a key contributor to tumo...

Automatic detection of sister chromatid exchanges using machine learning models and image analysis algorithms.

Scientific reports
After DNA replication, two chromatids with identical genetic information are formed in organisms; these are called sister chromatids. Sister chromatid exchange (SCE) is a recombination event between genetically equivalent sequences. Since no genetic ...

Integrating machine learning and time-to-event models to explain and predict risk of hospitalization due to dengue in Colombia.

Scientific reports
Arboviral diseases such as dengue pose major public health challenges in endemic regions, notably in Norte de Santander (Colombia), where they place substantial pressure on healthcare services. We analyzed 8,814 confirmed dengue cases reported to the...

Evaluating machine learning models and imputation strategies for Air Quality Index forecasting in urban India.

Environmental monitoring and assessment
Accurate Air Quality Index (AQI) prediction is essential for timely health risk management in urban environments, yet challenges such as missing data and complex pollutant interactions limit the performance of traditional approaches. This study inves...

Preoperative plasma ceramide profiling coupled with machine learning accurately predicts recurrence of hepatocellular carcinoma after resection.

Lipids in health and disease
BACKGROUND: Accurate stratification of recurrence risk after curative resection remains a critical challenge in the management of hepatocellular carcinoma (HCC). Dysregulated ceramide (CER) metabolism has been implicated in HCC progression and relaps...

TXSelect: A multi-task learning model to identify secretory effectors.

PLoS computational biology
Secretory effectors from pathogenic microorganisms significantly influence pathogen survival and pathogenicity by manipulating host signalling, immune responses, and metabolic processes. However, because of sequence and structural heterogeneity among...